| The phenomenon of clustering of innovation activities has always been the focus of domestic and international research.With the improvement of data availability,the spatial scale of scholars studying innovation agglomeration phenomenon has been gradually reduced.However,on the one hand,existing studies on innovation agglomeration in China are usually grouped by regions,but rarely by cities;on the other hand,due to the difficulty of obtaining basic data,existing studies on innovation agglomeration in China are mostly at the provincial scale,and the few studies that go deeper into the city scale only analyze innovation output indicators.To this end,this paper enriches the study of innovation agglomeration at the city scale from these two aspects.The research contains four parts: First,since innovation-centered cities are the agglomeration of innovation activities,cities are divided into innovation-centered cities and non-centered cities according to the hierarchy,and the research perspective is shifted from cities to innovation-centered cities,and the research content is shifted to the basic characteristics of the evolution of innovation-centered cities,and the research results demonstrate the agglomeration phenomenon of innovation activities.Second,based on the new economic geography theory,the formation and impact of innovation-centered cities are analyzed in terms of theoretical models,i.e.,how innovation activities cluster in innovation-centered cities and the impact of this clustering process are studied theoretically.Third,we estimate the complete urban R&D expenditure series by combining provincial and partial-year urban R&D expenditure data,which solves the problem of difficulty in obtaining urban R&D expenditure data,and account for the R&D capital stock as innovation input and innovation output per unit of R&D capital stock as innovation efficiency based on the urban R&D expenditure series,and the accounting results are the basic data for this study.Fourth,combining the idea of economic growth accounting and city data,we analyze the formation and impact of innovation-centered cities in terms of empirical research,aiming to answer whether innovation-centered cities are formed by recklessly efficient resource stacking or efficiency-driven resource clustering,and whether the impact of innovation development of innovation-centered cities on the innovation development of non-centered cities is dominated by spillover or siphon effect.Specifically.First,this paper combines the idea of the law of rank-order scale and urban innovation output data to delineate innovation centers,sub-centers and edge cities over the years,and to investigate the basic characteristics of innovation center city evolution.The results show that(1)from 1991 to 2019,the number of innovation center cities expanded from 4 to 18.On average,74.8% of innovation center and sub-center cities are located in the east,showing an obvious distribution imbalance.(2)It is difficult to shift upward and easy to shift downward in urban innovation output rank,and there is significant city rank heterogeneity and regional heterogeneity in upward or downward shift,but the overall trend of urban innovation output rank is upward,and cities at all levels are approaching the first city.(3)It is extremely difficult and time-consuming to move from innovation-edge cities to central cities.Second,this paper constructs a three-sector new economic geography model to theoretically study the formation and impact of innovation-centered cities,and finds that:(1)innovation clustering occurs significantly when driven by the market.Under larger shocks,the location of innovation agglomeration will change.(2)Innovation inputs and innovation efficiency jointly explain the total innovation output,i.e.,the formation of innovation centers.(3)Innovation center cities inhibit the innovation development of non-center cities by clustering innovation factors on the one hand,and drive the innovation development of non-center cities through knowledge spillover and increasing total knowledge on the other hand.Again,this paper estimates the R&D expenditure series of 289 cities in China from 2000-2019 by combining provincial R&D expenditure and urban R&D expenditure data in some years.Further,this paper compares the R&D capital stock estimation methods in the existing literature and uses the BEA method to estimate the urban R&D capital stock.Based on the estimated R&D capital stock,this paper investigates the convergence characteristics of urban R&D capital stock.The results find that the overall R&D capital stock of Chinese cities converges significantly,but the convergence rate is slow,and there is significant regional,city-area,and time-stage heterogeneity.Finally,this paper uses city panel data to empirically analyze the formation mechanism and spillover effects of innovation center cities.First,this paper uses city R&D capital stock estimation data to study the mechanism of innovation center city formation from the perspective of R&D investment.The results show that:(1)innovation investment continues to cluster in the eastern region and the five major city clusters,and most new innovation center cities appear in the eastern region and the five major city clusters during the same period;(2)innovation investment tends to cluster in the central region in recent years,and several new innovation sub-center cities appear in the central region during the same period;(3)the share of innovation investment in the northeast region continues to decline nationwide,and some cities in the northeast region withdraw from the(3)the share of innovation investment in Northeast China has been decreasing,and some cities in Northeast China have withdrawn from the ranks of innovation center cities.All of these results suggest that R&D capital stock clustering can explain the formation of innovation center cities.In addition,from the results of various empirical models constructed in this paper,R&D capital stock agglomeration can explain at least 1/3 of the innovation output agglomeration in the sample period of this paper.Second,this paper explores the mechanism of innovation center city formation at the level of R&D efficiency.This paper measures the innovation efficiency of the whole country,14 major city clusters,and each city from 2000-2018,analyzes the relationship between innovation efficiency and the creation and exit of innovation center cities,investigates whether R&D capital flows to regions with higher innovation efficiency,and also explores the influencing factors of innovation efficiency.The results show that(1)the innovation efficiency of Beijing-Tianjin-Hebei city cluster and Liaoning-Zhongnan city cluster is lower,which can explain the decline of Beijing’s innovation investment share in the country;(2)the innovation efficiency of Yangtze River Delta city cluster and Guangdong-Hong Kong-Macao Greater Bay Area are the top two of the traditional five city clusters,which can explain the concentration of R&D capital stock to Yangtze River Delta city cluster and Guangdong-Hong Kong-Macao Greater Bay Area.(3)The core cities of the city clusters with the highest innovation efficiency are all located in the eastern and central regions,which can explain the clustering of R&D capital stock in the eastern and central regions.(4)The narrowing of the differences in R&D capital stock within city clusters and the accumulation of physical capital stock are important reasons for the rise of innovation efficiency in city clusters.Further provincial,hierarchical,and city-level results indicate that R&D capital stock flows from less efficient regions to more efficient ones.The city-level study also finds that the cohort effect,physical capital stock,and R&D capital stock are important explanatory factors for the differences in innovation efficiency among cities.Third,this paper constructs a spillover effect model to study the main paths of innovation spillover effect.The results find that the innovation spillover effect mainly exists in the province.Further,since the provincial capital cities are the provincial innovation center cities,this paper estimates the innovation spillover effect in the provincial capital cities and explains the size of the spillover effect through innovation cooperation,innovation base and innovation efficiency.The results show that(1)provincial capital cities have a significant positive impact on innovation in other cities in the province.(2)Provincial capital cities have greater innovation quantity and quality spillover effects on cities with better innovation bases.The development of innovation quality in provincial capital cities inhibits the development of innovation quality in cities with weak innovation bases,which shows a siphon effect.The quality of innovation spillover effect of provincial capital cities to cities with which they have carried out collaborative innovation is greater,and the quantity spillover effect is smaller.(3)The innovation development of provincial capital cities is conducive to the innovation efficiency improvement of local cities,which in turn promotes the innovation development of local cities.Based on the obtained research findings,this paper argues that building innovation center cities as well as coordinating innovation development should be strengthened by considering the following aspects: maintaining the vitality of Beijing-Tianjin-Hebei city cluster,Yangtze River Delta city cluster and Guangdong-Hong Kong-Macao Greater Bay Area is crucial;vigorously building central innovation center cities and giving full play to the demonstration effect of urban innovation;guiding western center cities to give full play to the technology diffusion effect and building a number of new sub-center cities;promoting economic recovery in the northeast requires stable R&D investment;strengthening regional cooperation to narrow the gap between the central and western regions and the northeast and the east;maintaining the stability of innovation policies and science and technology policies;attaching importance to physical capital investment;coordinating the development within urban clusters;and attaching importance to the siphoning effect of large cities on small cities. |
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